AI-displaced workers face one-month rehiring lag

Goldman Sachs economist Pierfrancesco Mei found AI-exposed workers displaced since 2025 took roughly one month longer to find work, TheStreet reported on Nov. 1, citing Fortune’s account of a Goldman research note.

The Goldman research note matters because those workers were about 10 percentage points more likely than other laid-off workers to remain unemployed one year after job loss, according to the Nov. 1 article.

Mei’s work uses the Labor Department’s Displaced Worker Supplement, a survey run every two years since 1984 alongside the Current Population Survey. The supplement tracks people after involuntary job losses, according to the Bureau of Labor Statistics.

The survey does not ask whether AI caused a layoff, so Goldman used a composite AI-exposure measure, a gauge of jobs with tasks more exposed to the technology. Goldman found no meaningful outcome gap before 2022, the period it treated as preceding wider AI adoption.

Mei linked the pattern to earlier technology shocks. In April 2026, he wrote that workers who lost jobs because of technology needed about one extra month to be rehired and earned more than 3% less in real terms after returning to work.

Older workers lag

Goldman’s age split shows the burden falling more heavily on midcareer and older workers. Displaced workers aged 35 and above in AI-exposed roles needed about five additional weeks to return to full-time work, compared with roughly three weeks for workers under 35.

Broader government data point in the same direction. The BLS said 7.4 million workers were displaced between January 2023 and December 2025, up from 6.3 million in the prior survey, and long-tenured workers aged 55 and older were less likely to be employed again by January 2026 than workers aged 25 to 54.

The pay recovery also weakened. Among long-tenured workers rehired into full-time roles, about 49% earned at least as much as before, down from about 62% in the previous survey, according to the figures cited in TheStreet.

Mei attributed part of the damage to occupational downgrading, meaning workers moved into jobs that used fewer of their analytical and interpersonal skills. Geoffrey Sanzenbacher of the Center for Retirement Research at Boston College found in June 2026 that older workers in highly AI-exposed occupations had been leaving jobs faster since ChatGPT’s late-2022 release, with many exits ending in unemployment rather than retirement.

Entry-level pressure

Goldman’s findings were less severe for younger displaced workers who already had jobs. The bank found they were less likely to take temporary work on the way back to full-time employment and less likely to rely on a second job, TheStreet reported.

The risk for younger workers may instead sit at the hiring stage. Stanford researchers using ADP payroll data found in August that employment for workers aged 22 to 25 in the most AI-exposed occupations was about 19% below where it would have been if it had tracked less-exposed peers, with the gap driven mainly by weaker hiring rather than layoffs.

Other research cited in the article points to similar entry-level pressure. Harvard researchers found firms adopting generative AI reduced junior headcount by about 7.7% within six quarters while senior staffing stayed steady, and a June GMAC survey found one-third of employers had used AI for some entry-level work instead of hiring a person.

Companies have also been citing AI more often when announcing cuts. Challenger, Gray & Christmas said employers cited AI in 120,136 announced job reductions through September, about 21% of all cuts and the top stated reason this year, though AI accounted for about 9% of cuts in September itself.

The evidence is not uniform. The Yale Budget Lab found little departure from prior employment trends when measuring jobs by AI exposure.

Goldman’s approach captures only workers who had a job before losing it, not positions that companies never create. On October 23, Atlas360 reported that Goldman’s Jan Hatzius warned AI could displace up to 9% of American workers, while fewer than one-quarter of firms were using AI in regular workflows.

Source: financial-news article, TheStreet, Nov. 1, 2026